R: Hunting in Pico Basile, Bioko Island, Equatorial Guinea.
Hunting
R Documentation
Hunting in Pico Basile, Bioko Island, Equatorial Guinea.
Description
Case study analysed in Bonat et. al. (2016) concernings
on data of animals hunted in the village of Basile Fang,
Bioko Norte Province, Bioko Island, Equatorial Guinea.
Monthly number of blue duikers and other small animals
shot or snared was collected for a random sample of 52 commercial
hunters from August 2010 to September 2013.
For each animal caught, the species, sex, method of capture and
altitude were documented. The data set has 1216 observations.
ALT - Factor five levels indicating the Altitude where
the animal was caught.
SEX - Factor two levels Female and Male.
METHOD - Factor two levels Escopeta and
Trampa.
OT - Monthly number of other small animals hunted.
BD - Monthly number of blue duikers hunted.
OFFSET - Monthly number of hunter days.
HUNTER - Hunter index.
MONTH - Month index.
MONTHCALENDAR - Month using calendar numbers
(1-January, ..., 12-December).
YEAR - Year calendar (2010–2013).
HUNTER.MONTH - Index indicating observations taken at
the same HUNTER and MONTH.
Usage
data(Hunting)
Format
a data.frame with 1216 records and 11 variables.
Source
Bonat, et. al. (2016). Modelling the covariance structure in
marginal multivariate count models: Hunting in Bioko Island.
Environmetrics, submitted.
Bonat, W. H. (2016). Multiple Response Variables Regression
Models in R: The mcglm Package.
Journal of Statistical Software, submitted.
Examples
library(mcglm)
library(Matrix)
data(Hunting, package="mcglm")
formu <- OT ~ METHOD*ALT + SEX + ALT*poly(MONTH, 4)
Z0 <- mc_id(Hunting)
Z1 <- mc_mixed(~0 + HUNTER.MONTH, data = Hunting)
fit <- mcglm(linear_pred = c(formu), matrix_pred = list(c(Z0, Z1)),
link = c("log"), variance = c("poisson_tweedie"),
power_fixed = c(FALSE),
control_algorithm = list(max_iter = 100),
offset = list(log(Hunting$OFFSET)), data = Hunting)
summary(fit)
anova(fit)